class_docstr: Augmenter that replaces words with typos. You can specify a typo_type: charmix, which
  does a combination of character-level modifications (delete, insert, substitute, &
  swap); keyboard, which swaps characters which those close to each other on the QWERTY
  keyboard; misspelling, which replaces words with misspellings defined in a dictionary
  file; or all, which will apply a random combination of all 4
class_docstr_tok: ["Augmenter","that","replaces","words","with","typos",".","You","can","specify","a","typo_type",":","charmix",",","which","does","a","combination","of","character-level","modifications","(","delete",",","insert",",","substitute",",","&","swap",")",";","keyboard",",","which","swaps","characters","which","those","close","to","each","other","on","the","QWERTY","keyboard",";","misspelling",",","which","replaces","words","with","misspellings","defined","in","a","dictionary","file",";","or","all",",","which","will","apply","a","random","combination","of","all","4"]
code: def _tokenizer(self, text: str) -> List[str]:
      return tokenize(text)
  
file_path: AugLy/augly/text/augmenters/typo.py
imports: import json
  from typing import List, Optional
  from augly.text.augmenters.utils import detokenize, get_aug_idxes, tokenize, validate_augmenter_params
  from augly.utils import pathmgr
  from augly.utils.libsndfile import install_libsndfile
  from nlpaug.augmenter.char import KeyboardAug, RandomCharAug
  from nlpaug.augmenter.word import WordAugmenter
  from nlpaug.util import Action, Method
label_desc: Use image node_id 5 for calling the TypoAugmenter obj's underlying member method code with example usage: obj._tokenizer(text) and returns: tokenize